COURSE INFORMATION Course Title: ECONOMETRICS II

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
ECO 312	B	6	4	0	0	4	6

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Egis Zaimaj , Tuesdays (8:30 - 12:00)
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Elective
Classroom and Meeting Time:	Thursdays (computer lab)
Course Description:	Theory and Economic application f the linear multiple regression model, identification and structural estimation in simultaneous models, analyzing of economic policy and forecasting.
Course Objectives:	To provide students with the skills required to research in economics and finance using more advanced econometric practices and models. Real Life applications are analyzed via the E-VIEWS econometric package. Laboratory sessions help students to gain knowledge and new skills in demonstrating and interpreting the results of various static and dynamic models.

COURSE OUTLINE

Week	Topics
1	Introduction to the: Course, Syllabus, Textbook and Evaluation Method.
2	Regression with Dummy Variables
3	Binary Dependent Variable, Discrete Dependent Variable
4	Heteroskedasticity
5	Weighted Least Square Estimation & Functional Form Misspecification
6	Application Exam Nr:1 (Computer-Based)
7	Midterm (Paper - Based)
8	Examples of Time Series Regression Models
9	Trends and Seasonality
10	Stationary and Weakly Dependent Time Series
11	Using Highly Persistent Time Series in Regression Analysis
12	Dynamic Complete Models and the Absence of Serial Correlation
13	Application Exam Nr:2 (Computer-Based)
14	Review for Final Exam

Prerequisite(s):	Financial Econometrics I
Textbook:	Wooldridge J.M.(2015). Introduction to Econometrics. Cengage Learning
Other References:	Lectures, Practical Sessions, Exercises
Laboratory Work:	Yes
Computer Usage:	Yes (E-views Software)
Others:	No

COURSE LEARNING OUTCOMES

1	To have skills to set up robust parsimonious econometric models.
2	To have the ability of testing specification of the model.
3	To have the required skills to analyze financial time series and related regressions.
4	To model multivariate relationships using either dynamic or static form.

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Bachelor in Business Informatics (3 years) Program

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	25
Project	1	15
Quiz	2	10
Final Exam	1	30
Other	1	10
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	3	48
Hours for off-the-classroom study (Pre-study, practice)	16	3	48
Mid-terms	1	16	16
Assignments	1	10	10
Final examination	1	18	18
Other	1	10	10
Total Work Load:			150
Total Work Load/25(h):			6
ECTS Credit of the Course:			6